Spatial modelling improves genomic evaluation in Tanzanian smallholder admixed dairy cattle.

Area of Science:

• Animal Genetics and Breeding
• Agricultural Science
• Genomic Evaluation

Background:

• Smallholder dairy systems face challenges in genetic improvement due to high phenotypic variance, diverse environments, and limited data.
• Accurate separation of genetic and environmental effects is difficult in small herds with low genetic connectedness.
• Genomic evaluation for Tanzanian smallholder dairy cattle requires methods to address these inherent limitations.

Purpose of the Study:

• To evaluate the impact of spatial variation modeling on genomic evaluation accuracy in Tanzanian smallholder dairy cattle.
• To improve the separation of genetic and environmental effects in genomic evaluations.
• To address challenges in genetic improvement within diverse smallholder farming systems.

Main Methods:

• Analysis of 19,375 test-day milk yield records from 1894 dairy cows across 1386 herds in Tanzania.
• Genomic relationship matrix construction using 664,822 SNP markers after quality control.
• Fitting a series of genomic best linear unbiased prediction (GBLUP) models, including herd and spatial effects using a Matérn covariance function.

Main Results:

• Significant spatial variation in milk yield was observed, not fully captured by herd effects alone.
• A model incorporating spatial effects improved the accuracy of breeding value estimation compared to models with only herd effects.
• Models without spatial effects led to underestimation or overestimation of breeding values in less or more favorable environments, respectively.

Conclusions:

• Accurate genomic evaluation in smallholder settings is challenging but achievable with advanced modeling techniques.
• Spatial modeling effectively maximizes data utilization and improves the distinction between genetic and environmental influences.
• Further research is needed to understand the complex environmental and genetic drivers of phenotypic variance in African smallholder dairy populations.